ForWarn: Detecting Forest Disturbance from Satellite in Near-Real-Time

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ForWarn: Detecting Forest Disturbance

from Satellite in Near-Real-Time

Examples of forest disturbance, or recovery, seen in the ForWarn forest change images

Forest disturbance events often display degrees of severity. Variation in rates of recovery can relate to ecological, or vegetative resilience.

Area of vegetative recovery from forest disturbance pre-2010

http://ews.forestthreats.org

Allegheny National Forest Hickory Creek Wilderness area Forest Change Assessment Viewer (FCAV) 09/13/2011 1-yr baseline

Allegheny National Forest Hickory Creek Wilderness area Landsat 7TM on 09/13/2011 , 453 RGB http://ews.forestthreats.org

forwarn.forestthreats.org

The Atchafalaya basin's forests thrive with seasonal flooding, yet high water is normally a spring phenomenon there. During the past month, unusually high water levels have inundated wetlands and forests along and near the Mississippi River basin. From space, floodwaters appear to decrease existing vegetation, as water masks low lying plant cover. According to the USGS, river discharge at Morgan City, Louisiana was 145,000 ft3/sec on January 16, 2012 compared to 84,000 ft3/sec the prior year. (See http://waterdata.usgs.gov.)

forwarn.forestthreats.org

ForWarn Quick Start Guide 1.

Open this URL in a web browser http://forwarn.forestthreats.org/fcav

2.

In the Table of Contents window, click on the tab heading “Forest Disturbance Detection Maps” to expand and view the data layers (NRT – near real time)

3.

By default, the most recent forest change image in the “All-Year” baseline will be displayed. This image is a result of comparing the most recent MODIS NDVI image to the maximum NDVI value over the entire MODIS NDVI history (12+ years), and shows all forest disturbances over the entire historical period.

4.

Turn-off the most recent “All-Year” baseline image and turn-on the most recent in the “1-Year” baseline group. This allows one to view only forest disturbance, or recovery, that has occurred within just the past one year (for this specific time period).

5.

Use the map controls to zoom and pan, or type the name of a county in the “Find Area” box in the topright area of the FCAV viewer window

6.

Use the ‘wrench’ icon to adjust the transparency of any layer to better view the basemap , or other layers

Table of Contents window expanded

forwarn.forestthreats.org/fcav

Application Limitation - Detection delay due to compositing method -

Three additional change products now available: (1) derived from an ‘Adaptive Length Compositing’ method, and (2) called Seasonally Adjusted, which mitigates annual seasonal variations in the timing of spring and fall

Application Limitation - Spatial resolution -

Application Limitation Awareness - “Edge-of-the-mask” mixed pixels -

Drought Sensitivity at the ‘edge-of-the-mask’

Forest Disturbance Assessment Layers

Forest Disturbance Assessment Process 1. Locate (understand geographic site and situation) – Land cover / land use (recent aerials) – Topographic position (in mountainous terrain elevation and aspect may be important, use topographic maps, hill shade)

2. Characterize (NDVI departure) – – – – – –

Progression speed and duration (fast vs. slow, obs. successive images) Severity, or percent NDVI change (positive or negative, light-to-heavy) Spatial extent (large area or localized) Pattern and shape (spotty/scattered, bulls-eye, target-like, linearity) Edges (hard, well defined or trails-off, feathers out with less departure) Seasonality (in spring and fall, the regional variation in annual phenology can cause NDVI departure, positive or negative )

3. Assess (using data layers in the Forest Change Assessment Viewer) – Use ancillary data layers in the ‘Viewer’ to vet disturbance or recovery – Reference ‘Disturbance Protocol’ document



NLCD-based “Masks”



New Open-Source “FCAV Viewer”



Clip, Zip and Ship functionality



Download data by point/line/polygon



User-shapefile upload



Disturbance auto-detect



Disturbance auto-notify via any social media format